Plasma metabolites related to cellular energy metabolism are altered in adults with Down syndrome and Alzheimer's disease.
Thomas J GrossEric DoranAmrita K CheemaElizabeth HeadIra T LottMark MapstonePublished in: Developmental neurobiology (2019)
Down syndrome (DS) is a well-known neurodevelopmental disorder most commonly caused by trisomy of chromosome 21. Because individuals with DS almost universally develop heavy amyloid burden and Alzheimer's disease (AD), biomarker discovery in this population may be extremely fruitful. Moreover, any AD biomarker in DS that does not directly involve amyloid pathology may be of high value for understanding broader mechanisms of AD generalizable to the neurotypical population. In this retrospective biomarker discovery study, we examined banked peripheral plasma samples from 78 individuals with DS who met clinical criteria for AD at the time of the blood draw (DS-AD) and 68 individuals with DS who did not (DS-NAD). We measured the relative abundance of approximately 5,000 putative features in the plasma using untargeted mass spectrometry (MS). We found significantly higher levels of a peak putatively annotated as lactic acid in the DS-AD group (q = .014), a finding confirmed using targeted MS (q = .011). Because lactate is the terminal product of glycolysis and subsequent lactic acid fermentation, we performed additional targeted MS focusing on central carbon metabolism which revealed significantly increased levels of pyruvic (q = .03) and methyladipic (q = .03) acids in addition to significantly lower levels of uridine (q = .007) in the DS-AD group. These data suggest that AD in DS is accompanied by a shift from aerobic respiration toward the less efficient fermentative metabolism and that bioenergetically derived metabolites observable in peripheral blood may be useful for detecting this shift.
Keyphrases
- mass spectrometry
- lactic acid
- ms ms
- multiple sclerosis
- small molecule
- gene expression
- dna methylation
- cancer therapy
- high resolution
- risk factors
- big data
- high performance liquid chromatography
- artificial intelligence
- capillary electrophoresis
- microbial community
- deep learning
- chemotherapy induced
- tandem mass spectrometry